rocketride-server

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GitHub Python MIT

Description

RocketRide Server is a high-throughput agent runtime designed for production-grade, low-latency LLM tool execution and orchestration.

Key Features

  • High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes
  • Built for RAG and agents with parsing, vectorization, retrieval, and execution nodes
  • Composable workflows where nodes are stitched as directed acyclic graphs
  • Production observability with built-in metrics, logs, and tracing integration
  • Multi-language SDK with Python-first and additional languages supported

Use Cases

💡 Build enterprise RAG systems that handle large-scale document ingestion and retrieval
💡 Compose multiple AI capabilities into observable agent pipelines
💡 Provide a unified pipeline abstraction for multi-model inference
💡 Schedule hybrid RAG + agent workflows under low-latency requirements

Quick Start

# Install RocketRide
pip install rocketride

# Define a RAG + agent workflow
from rocketride import Pipeline, nodes

pipe = Pipeline()
pipe.add(nodes.DocumentLoader(source="docs/"))
pipe.add(nodes.Embedder(model="text-embedding-3-small"))
pipe.add(nodes.VectorStore(name="kb"))
pipe.add(nodes.AgentNode(llm="claude-sonnet-4"))

# Execute
result = pipe.run(query="Summarize the product FAQ")

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